Fusion trees for fast and accurate classification of hyperspectral data with ensembles of γ-divergence-based RBF networks.
Uwe KnauerAndreas BackhausUdo SeiffertPublished in: Neural Comput. Appl. (2015)
Keyphrases
- accurate classification
- rbf network
- hyperspectral data
- hyperspectral
- hyperspectral images
- radial basis function
- decision trees
- hyperspectral imagery
- multispectral
- classification algorithm
- classification accuracy
- supervised learning
- remote sensing
- random projections
- infrared
- rbf neural network
- learning algorithm
- data fusion
- back propagation
- learning tasks
- principal components
- feature selection
- target detection
- image processing
- ensemble methods
- image data
- data mining
- artificial neural networks
- multilayer perceptron
- satellite images
- training data
- training algorithm
- data sets
- support vector machine
- fusion method
- neural network
- dimension reduction
- clustering algorithm
- training set
- multispectral images
- knn